amulyabhagwat1999@gmail.com

@Amulya171999·15 public vizzes

aera chart 2

This example visualizes the population trends of the world and its major areas over time with an area chart. Multiple filled areas represent different countries or regions, using a categorical color scale for distinction. The chart is rendered as an SVG, with axes, gridlines, and a legend for identification. The implementation uses d3.scaleTime, d3.scaleLinear, d3.area, and d3.axisBottom, with data fetched from a CSV source and processed for display.

Jul 12, 2024

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Fork of aera chart 2

This area chart shows population trends over time for the world and its major areas, with each series distinguished by color and accompanied by a legend. The visualization uses D3 v6 with SVG rendering, employing `d3.area` with `curveMonotoneX` for smooth paths and `d3.scaleTime` and `d3.scaleLinear` for axes. Data comes from a CSV file processed into date-value pairs. Gridlines, axis labels, and a bold title provide context, while ordinal color scaling differentiates regions.

Jul 12, 2024

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Fork of aera chart test

This area chart visualizes population trends over years for the World and its major areas, using distinct colors per country. Built with D3.js, it employs `scaleTime` and `scaleLinear` for axes, a `d3.area()` generator with a monotone curve, and `axisBottom`/`axisLeft` for ticks. Data is fetched from a CSV URL and processed via `timeParse`. The SVG output includes gridlines, a title, and a legend, rendered with a color scale from `schemeCategory10`.

Jul 12, 2024

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area chart

This example shows a stacked area chart of population trends over time for multiple groups, with a legend identifying each series. It loads CSV data from a GitHub gist, using `d3.csv`, and renders the chart as SVG. The code uses `d3.stack` to compute layered series, `d3.area` with `y0` and `y1` accessors to generate paths, and `d3.scaleOrdinal` with `d3.schemeSet2` for colors. Axes are drawn with `d3.axisBottom` and `d3.axisLeft`, with data-driven tick formatting via `d3.format`.

Jul 11, 2024

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amulya_test

This example uses the D3.js library to render a multi-series area chart showing population changes over time for multiple countries. The visualization loads data from a CSV file and processes it into time-series form, with each country's values mapped to a smooth monotone curve. The chart includes computed axes, a categorical color scheme, and a legend to distinguish between the countries. The code demonstrates D3's modular API, including `scaleTime`, `area`, and `axisBottom`, alongside custom ES6 modules for data processing.

Jul 11, 2024

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Fork of Assignment 2 part2

This area chart shows population trends for multiple countries over time, using a time-scaled x-axis and a linear y-axis. The visualization is built with d3.js, leveraging `d3.scaleTime`, `d3.scaleLinear`, and `d3.area` to render the filled paths, with a categorical color scale (`d3.scaleOrdinal`) distinguishing each country. Data is loaded from a remote CSV file and processed into a date-value format. The chart includes axes, a legend, and uses an SVG rendering approach.

Jul 11, 2024

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Fork of Hello VizHub

This example demonstrates an area chart visualizing population data across multiple countries over time, with a legend identifying each series. It loads CSV data from a GitHub gist and processes it with a local ES6 module. The chart uses D3 v6 APIs including `d3.csv`, `d3.scaleOrdinal`, `d3.area`, and `d3.axisBottom`/`d3.axisLeft`, while rendering via SVG. The reusable `areaChart` module exports a configurable function, and the visualization applies `schemeCategory10` for colors and `curveMonotoneX` for smoothing.

Jul 11, 2024

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test10

This area chart displays population trends for multiple countries over time, with each country represented by a colored filled area and a corresponding legend. The visualization is built using D3.js, specifically employing `d3.scaleTime`, `d3.scaleLinear`, `d3.area`, and `d3.axisBottom`/`d3.axisLeft` for rendering. Population data is fetched from a CSV file and processed into date-value pairs, while the color scale uses `d3.scaleOrdinal` with `schemeCategory10`. The chart is rendered as an SVG with customizable dimensions and margins.

Jul 11, 2024

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Fork of test

This area chart visualizes population trends over time for multiple countries, using filled paths to compare growth patterns across categories. Built with D3 v6, the code loads CSV data from a GitHub gist, processes it into time-series values, and renders axes and colored areas via `d3.area` and `d3.curveMonotoneX`. A categorical color scale and legend identify each country, while the chart is generated as SVG with custom margin and sizing options.

Jul 11, 2024

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test

This example displays population changes over time for multiple countries as overlapping area charts. It loads CSV data from a GitHub gist, parses the year columns, and renders the visualization using D3 v6 APIs including `d3.scaleTime`, `d3.scaleLinear`, `d3.area`, and `d3.curveMonotoneX`. A categorical color scale assigns hues per country, with a legend positioned to the right. The SVG output is generated via a reusable chart function and D3 selection methods.

Jul 11, 2024

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Fork of Assignment 2 part2

This area chart visualizes population trends across multiple countries over time, with each country represented by a filled area path. The data comes from a CSV file containing yearly population figures, processed into chronological series using d3.csv and custom data transformation. The visualization employs d3.area(), d3.scaleTime(), and d3.scaleLinear() for rendering, along with d3.axisBottom() and d3.axisLeft() for axes. A categorical color scale (d3.scaleOrdinal with schemeCategory10) distinguishes countries, while a legend identifies each series. The chart is rendered as SVG with configurable width, height, and margins through a reusable areaChart() function.

Jul 11, 2024

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Fork of Fork of Hello VizHub

This fork of Hello VizHub displays a multi-series area chart rendered as SVG, with axes, tick labels, and a bold title. It loads D3 from UNPKG and uses `import` to access `d3.scaleTime`, `d3.scaleLinear`, `d3.area`, `d3.axisBottom`, and `d3.axisLeft` for chart construction, while a local ES6 module supplies the message. The example demonstrates importing from both external and local modules.

Jul 11, 2024

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Fork of Fork of Hello VizHub

This area chart displays population trends for the world and major regions from 1750 to 2150, using an SVG rendered with D3.js. The code imports D3 via ES6 modules, loads CSV data from a GitHub gist, and parses years with `d3.timeParse`. It applies `d3.area` with a monotone curve, `d3.axisBottom` and `d3.axisLeft` for axes, and `d3.scaleOrdinal` for categorical coloring. Legends and a title are appended as SVG elements, demonstrating modular chart configuration with D3 methods.

Jul 11, 2024

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Fork of Hello VizHub

This fork of Hello VizHub displays an area chart of world population estimates from 1750 to 2150, with multiple series distinguished by color. It loads data from a remote CSV file and renders the visualization as SVG, using D3’s `d3.area`, `d3.scaleLinear`, `d3.axisBottom`, `d3.axisLeft`, and `d3.curveMonotoneX` to build the chart. The example also demonstrates ES6 module imports from D3 and local files, along with a custom chart factory function.

Jul 11, 2024

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Fork of Assignment 2 part2

This area chart visualizes the population trends of the world and its major areas from 1750 to 2150, using a stacked area representation. The chart is rendered as SVG, with data parsed from a CSV file via `d3.csv`. It uses `d3.scaleLinear` for both axes, `d3.stack` to layer the series, and `d3.area` to generate the area paths. A color legend, built with `d3.scaleOrdinal` and `d3.schemeCategory10`, distinguishes the different population categories.

Jul 11, 2024